Abstract
We present an adaptive strategy for a group of robots engaged in the localization of multiple targets. The robotic search algorithm is inspired by chemotaxis behavior in bacteria, and the algorithmic parameters are updated using a distributed implementation of the Particle Swarm Optimization technique. We explore the efficacy of the adaptation, the impact of using local fitness measurements to improve global fitness, and the effect of different particle neighborhood sizes on performance. The robustness of the approach in non-static environments is tested in a time-varying scenario.
Preview
Unable to display preview. Download preview PDF.
Similar content being viewed by others
References
Balch, T.: Behavioral diversity in learning robot teams. PhD Thesis, College of Computing, Georgia Institute of Technology (1998)
Berg, H.C.: E. coli in motion. Springer, NY (2003)
Cianci, C., Raemy, X., Pugh, J., Martinoli, A.: Communication in a swarm of miniature robots: The e-puck as an educational tool for swarm robotics. In: Şahin, E., Spears, W.M., Winfield, A.F.T. (eds.) Swarm Rob. Workshop. LNCS, vol. 4433, pp. 103–115. Springer, Heidelberg (2007)
Dhariwal, A., Sukhatme, G.S., Requicha, A.A.G.: Bacterium-inspired robots for environmental monitoring. In: Proc. of the IEEE Intl. Conf. on Robotics and Automation, New Orleans, LA, USA, April 26 - May 1, 2004, pp. 1436–1443 (2004)
Doctor, S., Venayagamoorthy, G.K., Gudise, V.G.: Optimal PSO for Collective Robotic Search Applications. In: Proc. of the IEEE Congress on Evolutionary Computation, Portland, OR, USA, June 19-23, 2004, pp. 1390–1395 (2004)
Goldsmith, S.Y., Robinett, R.: Collective search by mobile robots using alpha-beta coordination. In: Drogoul, A., Tambe, M., Fukuda, T. (eds.) Collective Robotics, pp. 136–146. Springer, Berlin (1998)
Hayes, A.T.: How Many Robots? Group Size and Efficiency in Collective Search Tasks. In: Proc. of the 6th Intl. Symp. on Distributed Autonomous Robotic Systems DARS 2002, pp. 289–298. Fukuoka, Japan (2002)
Hayes, A.T., Martinoli, A., Goodman, R.M.: Swarm Robotic Odor Localization: Off-Line Optimization and Validation with Real Robots. In: McFarland, D. (ed.) Special Issue on Biological Robots. Robotica, vol. 21, pp. 427–441 (2003)
Holland, O., Melhuish, C.: Some adaptive movements of animats with single symmetrical sensors. In: 4th Intl. Conf. on Simulation of Adaptive Behaviour. MIT Press, Cambridge (1996)
Kantor, G., Singh, S., Peterson, R., Rus, D., Das, A., Kumar, V., Pereira, G., Spletzer, J.: Distributed search and rescue with robot and sensor teams. In: Proc. of the 4th Intl. Conf. on Field and Service Robotics, Japan (2003)
Kelly, I.D., Keating, D.A.: Faster learning of control parameters through sharing experiences of autonomous mobile robots. Intl. J. of System Science 29(7), 783–793 (1998)
Kennedy, J., Eberhart, R.: Particle swarm optimization, Neural Networks. In: Proceedings, IEEE Intl. Conf., vol. 4, pp. 1942–1948 (1995)
Marques, L., Nunes, U., de Almeida, A.T.: Olfaction-based mobile robot navigation. Thin Solid Films 418, 51–58 (2002)
Matarić, M.J.: Learning in behavior-based multi-robot systems: Policies, models, and other agents. In: Sun, R. (ed.) Special Issue on Multi-disciplinary studies of multi-agent learning. Cognitive Systems Research, vol. 2(1), pp. 81–93 (2001)
Michel, O.: Webots: Professional Mobile Robot Simulation. Int. J. of Advanced Robotic Systems 1, 39–42 (2004)
Ögren, P., Fiorelli, E., Leonard, N.E.: Cooperative Control of Mobile Sensor Networks: Adaptive Gradient Climbing in a Distributed Environment. IEEE Transactions on Automatic Control 49(8), 1292–1302 (2004)
Osuka, K., Murphy, R., Schultz, A.C.: USAR Competitions for Physically Situated Robots. IEEE Robotics and Automation Magazine, 26–33 (September 2002)
Pugh, J., Zhang, Y., Martinoli, A.: Particle swarm optimization for unsupervised robotic learning. In: Swarm Intelligence Symp., Pasadena, CA, pp. 92–99 (2005)
Pugh, J., Martinoli, A.: Multi-Robot Learning with Particle Swarm Optimization. In: Intl. Conf. on Autonomous Agents and Multiagent Systems, Hakodate, Japan, May 8-12, 2006, pp. 441–448 (2006)
Pugh, J., Martinoli, A.: Relative Localization and Communication Module for Small-Scale Multi-Robot Systems. In: Proc. of the IEEE Intl. Conf. on Robotics and Automation, Miami, Florida, USA, May 15-19, 2006, pp. 188–193 (2006)
Stone, P.: Layered Learning in Multi-Agent Systems. PhD Thesis, School of Computer Science, Carnegie Mellon University (1998)
Author information
Authors and Affiliations
Editor information
Rights and permissions
Copyright information
© 2008 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Pugh, J., Martinoli, A. (2008). Distributed Adaptation in Multi-robot Search Using Particle Swarm Optimization. In: Asada, M., Hallam, J.C.T., Meyer, JA., Tani, J. (eds) From Animals to Animats 10. SAB 2008. Lecture Notes in Computer Science(), vol 5040. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-69134-1_39
Download citation
DOI: https://doi.org/10.1007/978-3-540-69134-1_39
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-69133-4
Online ISBN: 978-3-540-69134-1
eBook Packages: Computer ScienceComputer Science (R0)